The probability density estimation of the number of software failures in the event of clustering or clumping of the software failures is the subject of this paper. A discrete compound Poisson (CP) prediction model, as opposed to a Poisson (P) process, is proposed for the random variable (rv) X(rem), which is the remaining number of software failures. The compounding distributions, which are assumed to govern the failure sizes at Poisson arrivals, are respectively taken to be geometric when failures are forgetful and logarithmic-series (LSD) when failures are contagious. The expected value (mu) of X(rem) of CP is calculated as a function of the time-dependent Poisson and compounding distribution based on the failures experienced. Also, the q (variance/mean) parameter for the remaining number of failures, q(rem) is best estimated by q(past) from the failures already experienced. Then, one obtains the pdf of the remaining number of failures estimated by CP(mu,q). The CP model suggests that the CP is superior to Poisson where clumping of failures exists. Its predictive validity is comparable to Musa-Okumoto's (MO) Log-Poisson Model for certain software failure data with q > 1 when software failures clump within the same CPU second or unit time.


A computer simulation of void dynamics under the action of electromigration and capillary forces in narrow thin interconnects
Ogurtani, TO; Oren, EE (2000-10-25)
In these studies a comprehensive picture of void dynamics in connection with the critical morphological evaluation has been thoroughly anticipated in order to understand main reasons as well as the conditions under which premature failure of metallic thin interconnects occur. Our mathematical model on diffusion and mass accumulation on void surfaces, under the action of applied electrostatic potential and capillary effects, follows a novel irreversible but discrete thermodynamic formulation of interphases a...
Improved Software Reliability Prediction by Using Model Stacking and Averaging
Karaomer, Rabia Burcu; Yet, Barbaros; CHOUSEİNOGLOU, OUMOUT (2019-01-01)
Software reliability is an important factor for the success of a software project. Accurate modelling of software reliability enables estimation of remaining defects, the timing of deployment and required future effort. These factors contribute to successful planning of project schedule and resources. A number of software reliability prediction models have been proposed, each with different assumptions regarding software defect introduction and discovery. The performances of these models differ depending on...
Software Functional Size: For Cost Estimation and More
Ozkan, Baris; Turetken, Oktay; Demirörs, Onur (2008-09-05)
Determining software characteristics that will effectively support project planning, execution, monitoring and closure remains to be one of the prevalent challenges software project managers face. Functional size measures were introduced to quantify one of the primary characteristics of software. Although functional size measurement methods have not been without criticisms, they have significant promises for software project management. In this paper, we explore the contributions of functional size measurem...
Domain Adaptation on Graphs via Frequency Analysis
Pilancı, Mehmet; Vural, Elif (2019-08-22)
Classical machine learning algorithms assume the training and test data to be sampled from the same distribution, while this assumption may be violated in practice. Domain adaptation methods aim to exploit the information available in a source domain in order to improve the performance of classification in a target domain. In this work, we focus on the problem of domain adaptation in graph settings. We consider a source graph with many labeled nodes and aim to estimate the class labels on a target graph wit...
Affect of shear strength criteria selection in probabilistic rock slope stability analyses: A case study for a jointed rock slope in Norway
Düzgün, Hafize Şebnem; Bhasin, R. K. (2007-05-31)
Probabilistic rock slope stability analyses are essential to risk assessments, as risk is defined by the probability of occurrence of an instability multiplied by the consequences of the failure. Usually, probabilistic rock slope stability problems are modeled using the Coulomb failure criterion since it is linear, providing simple modeling algorithms. It is acknowledged widely that rock slope stability problems may exhibit non-linear failure behavior, leading to consideration of non-linear limit equilibriu...
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